New ST-segment elevation myocardial infarction criteria for left bundle branch block based on QRS area

Area of Science:

• Cardiology
• Medical Imaging
• Algorithm Development

Background:

• Detecting ST-segment elevation myocardial infarction (STEMI) with left bundle-branch block (LBBB) on ECG is challenging due to altered conduction causing ST deviation.
• Existing algorithms for STEMI detection in LBBB have limitations in balancing sensitivity and specificity.

Purpose of the Study:

• To introduce a novel algorithm for STEMI detection in the presence of LBBB.
• To compare the performance of the new algorithm against three established criteria: Sgarbossa, Selvester 10% RS, and Smith 25% S-wave.

Main Methods:

• The study analyzed ECG data from 143 acute myocardial infarction (MI) patients and 239 controls, with LBBB identified by computer interpretation.
• A new algorithm utilizing an ST threshold based on QRS area was developed and compared with Sgarbossa, Selvester, and Smith criteria.
• Performance was evaluated using sensitivity, specificity, and positive likelihood ratio (LR+), with variations tested for single and 2-lead requirements.

Main Results:

• Algorithm performance varied, with the Sgarbossa score (≥3) showing the lowest sensitivity (13.3%) and highest specificity (97.9%).
• The Selvester 10% rule demonstrated the highest sensitivity (30.1%) but lower specificity (93.2%).
• The novel Philips QRS area (23.8% sensitivity, 95.8% specificity) and Smith S-wave (20.3% sensitivity, 94.9% specificity) algorithms performed intermediately.

Conclusions:

• Discordant ST elevation criteria enhance STEMI detection sensitivity in LBBB but can reduce specificity.
• The Selvester algorithm is preferable for applications prioritizing high sensitivity in STEMI detection.
• For scenarios demanding low false positive rates, such as pre-hospital activation for urgent PCI, the Philips QRS area or Smith 25% S-wave algorithms may be more suitable.